Abstract

The aim of this research is to discover the continuance and recommendation intention of higher education students who are using ChatGPT. Specifically, we proposed an extend technology continuance theory (TCT) by integrating the recommendation intention. A structured Google form is used to collect the data from the higher education students especially engineering college students in India. A sum of 307 responses gathered and employed for the purpose of data analysis. Structured equation model (SEM) was used to test the research hypothesis. The study found that perceived usefulness, attitude, and satisfaction were significant predictors of continuance intention, while satisfaction and continuance intention themselves predicted recommendation intention, indicating that students who perceive ChatGPT as useful, have a positive attitude towards it, and are satisfied with it are more likely to continue using it and recommend it to others. These results underscore the importance of user satisfaction and positive attitudes in fostering continued engagement and advocacy for AI-driven chat systems. The study’s findings were evaluated in terms of their discussion, limitations and implications for future research.

中文翻译：

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印度高等教育学生 ChatGPT 的持续性和推荐意愿的实证证据：扩展的技术持续性理论

摘要

本研究的目的是发现正在使用 ChatGPT 的高等教育学生的继续和推荐意图。具体来说，我们通过整合推荐意图提出了扩展技术连续性理论（TCT）。使用结构化的谷歌表格来收集印度高等教育学生尤其是工程学院学生的数据。总共收集并采用了 307 份回复用于数据分析。使用结构化方程模型（SEM）来检验研究假设。研究发现，感知有用性、态度和满意度是持续意向的显着预测因素，而满意度和持续意向本身则预测推荐意向，这表明认为 ChatGPT 有用、对其持积极态度并对其感到满意的学生更有可能继续使用它并将其推荐给其他人。这些结果强调了用户满意度和积极态度对于促进人工智能驱动的聊天系统的持续参与和宣传的重要性。该研究的结果根据其讨论、局限性和对未来研究的影响进行了评估。